{"id":"W2430397844","doi":"10.1039/c6mb00237d","title":"Systems level analysis of the <i>Chlamydomonas reinhardtii</i> metabolic network reveals variability in evolutionary co-conservation","year":2016,"lang":"en","type":"article","venue":"Molecular BioSystems","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biological and Environmental Research; Office of Science; Royal Society of Chemistry; National Institute of General Medical Sciences; Medical Research Council; Royal Society; U.S. Department of Energy; Gordon and Betty Moore Foundation; Life Sciences Research Foundation; New York University Abu Dhabi; York University","keywords":"Chlamydomonas reinhardtii; Biology; Metabolic network; Phylogenetic tree; Computational biology; Gene; Chlamydomonas; Gene regulatory network; Evolutionary biology; Robustness (evolution); Systems biology; Phylogenetics; Organism; In silico; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001558937,0.0001977014,0.0004253167,0.0001313897,0.00005383854,0.00001314729,0.0002813603,0.0002115125,0.000005143898],"category_scores_gemma":[0.000331794,0.0001278,0.0002670235,0.001028056,0.00008021354,0.000006644678,0.00007676428,0.00007170043,0.000003052011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003846168,"about_ca_system_score_gemma":0.00006487096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003017913,"about_ca_topic_score_gemma":0.00004761598,"domain_scores_codex":[0.9977756,0.0006360231,0.0005975776,0.0004761354,0.0002349841,0.0002796569],"domain_scores_gemma":[0.9986218,0.00001959658,0.0002586421,0.0008804674,0.0001708133,0.00004870919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002850553,0.00003557351,0.03276769,0.0000442688,0.0003751834,7.694121e-7,0.000008483859,0.00268445,0.9619951,0.0008997013,0.001021307,0.0001390251],"study_design_scores_gemma":[0.0007742614,0.00005676151,0.1725534,0.0002301413,0.0005912523,0.0000259881,0.00001745609,0.0007777964,0.7874587,0.00006591284,0.03697068,0.0004776671],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827222,0.002724572,0.01275085,0.0002464455,0.0007327697,0.0005024569,0.0001700489,0.00001741256,0.000133227],"genre_scores_gemma":[0.9988707,0.0001018153,0.0001849618,0.00006940435,0.000255638,0.00004543606,0.00006933936,0.0000199895,0.0003827391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1745364,"threshold_uncertainty_score":0.5211534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009621159048174075,"score_gpt":0.2219121350399055,"score_spread":0.2122909759917314,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}